There are three main processes for the large-scale processing of food. Aseptic processing heats essentially fluid food and drink products to a suitable pasteurization temperature and then deposits them into suitably sterilized containers within an essentially aseptic environment.
Retorting uses the combination of heat and pressure to pasteurize or sterilize a food product essentially sealed within its container. The most common form of retorting is batch retorting where fixed quantities (by weight, size or volume) of product are processed under essentially identical process conditions within a static, usually single, processing vessel. A more recent variant, continuous retorting, moves batches of product through a series of vessels or chambers, each having as a series of set processing parameters.
Hydrostatic sterilizers undertake a similar process to continuous retorting but the product is passively moved through a static processing system comprised of several towers or chambers, each having a specific set of processing parameters which in combination achieve the necessary sterilization of the product and its container. Unlike retorting, the product moves individually and continuously through the chambers, not in batches.
There are many variants of these general processes such as the different methods of moving the product through the system, e.g. using product carriers attached to chain drives as in the Stork™ Hydrostat® or a helical rotation of the product through a processing vessel as in the FMC continuous Rotary® system.
While such processing systems are generally applied to larger-volume product requiring sterilization or pasteurization, many other products only require to be stabilized for improved shelf-life. Such treatment usually requires the inactivation of product components such as enzymes, oxidants or spoilage micro-organisms, which, if left untreated, would eventually lead to product spoilage. Typical examples are fresh fruits and vegetables to be converted to a form suitable for frozen or refrigerated storage, or processed products, such as ready meals, for chilled storage.
However, no matter which process is used or which products the process treats, to achieve the necessary processing state, i.e. sterilized, pasteurized or stabilized, the product must be subjected to a defined time-temperature-pressure treatment sufficient to ensure that every part of the product receives, at least, the minimum amount of energy to achieve a necessary minimum level of total micro-organism and/or enzyme lethality. Total lethality targets are usually defined by the appropriate regulatory bodies such as USDA and FDA in the USA and Food Standards Authorities in the European Union.
During any processing operation, there is almost always one location within the food container that for physical, and/or chemical and/or biochemical reasons is the last to reach the required temperature and therefore the last to be effectively processed. This is usually defined as the product ‘cold spot’. The Lethality target is directed at this location as it is assumed that this location is, from a product safety perspective, the least safe within the product. However, there are several obvious problems with such an assumption.
Firstly, it assumes that the product within the container displays minimal variation with regard to process performance. It is well-known, not only to those skilled in the art, but also anyone who has been involved with almost any aspect of food and drink product manufacture that there is tremendous variation in the composition and physical properties of the same item, even when produced ostensively from identical raw materials under similar conditions. The greater the complexity of the product, the greater the potential for such variation. Liquid-only products show the smallest variation, multiple component solid/liquid products show the greatest.
Such variation is acknowledged by food regulatory authorities and flexibility within labeling regulations reflect this. Products labels have to show a total composition, with its total composition broken down to a % content of major components such as protein, fat, carbohydrate, etc. In many instances, while major components such as meat in meat products and sugar content in jams, etc., have to show a % content, the figures quoted only need to be ‘typical averages’. Additionally, the regulations allow 20%-25% overstatement of protein content and a similar understatement in fat, sugar and moisture content. While this variability has a significant effect on nutritional quality, it can have a major influence on heat transfer properties, and thus product processing requirements.
A further basic labeling requirement is the statement of ‘net weight’, i.e. the weight of product after the product container is accounted for. Manufacturers generally overcome variations in weight by adopting a ‘minimum weight’ or a deliberate ‘giveaway’ approach, whereby only underweight product/container combinations are ejected. A recent study by Conway et al (2004) showed that more than 60% of a large sample of food items were out of compliance with their stated label contents and more than 15% were significantly out of compliance with their stated total weights. Both sources of variation can have a significant effect on processing performance, particularly the minimum lethal heat requirement and thus the safety of the processed food.
Secondly, in designing a processing methodology, it is also assumed that all parts of the process perform with equal and reproducible performance. It also known by those skilled in the art that few if any food processing systems have homogeneity of performance either within or between batches of product or between or within process segments.
Between batches variation can be due to a range of conditions including, but not limited to, product storage temperature and/or length of storage time prior to processing, product processing conditions, especially temperature range and variation, raw material compositional variation, raw material physical and chemical property variation, product weights, container weights, variation in dead-space volume, container compositional variation, especially liquid to solid ratio, stacking and packing configuration variation between batches, product temperature entering the processing system, product temperature leaving the processing system, storage time-temperature conditions following processing, etc. Additional variability in external, environmental and within process conditions will also contribute to between batch variability.
Variations within batch variation can be due to a range of conditions including, but not limited to all those previously described for between batch variation but also variation in processing conditions within the process system. Because few, if any of these variations will show up in conventional process monitoring, providing the input energy availability meets minimum requirements, there is often little indication that anything is wrong with the finished product as the process appears to be functioning as predicted and anticipated.
Thirdly, in addition to the variability of system performance, product composition and homogeneity, there is the rate of energy transfer and the variability of that energy transfer rate. We have shown (U.S. Patent Application 61/488,220, hereinafter incorporated by reference) that many physical factors affect the rate at which thermal energy is transferred from an outside energy source into the container while different factors affect the rate at which this thermal energy is transferred through the foodstuff and between the individual components comprising the foodstuff. We have also shown that various actions can be taken before, during and after processing which will both enhance the rate of transfer and improve the uniformity of its distribution.
Similarly, we have also shown (U.S. Patent Application 61/478,190, hereinafter incorporated by reference) that applying a range of physical actions to the container before, during and after processing can also enhance the efficiency of thermal transfer and its uniformity of distribution.
A typical example of how a process controller for a continuous Hydrostatic system measures, monitors and controls the process is described in U.S. Pat. No. 6,440,361 to Weng who also details many of the advances and variants of finite element analysis models that are used to produce predictive processing algorithms.
In summary, this and virtually all such similar programs rely on sensor measurement of water temperatures at various locations within the processing system, water levels, conveyor speeds, etc. Weng also states that the predictive process temperature profile is based on a measurement of the initial product temperature. Unfortunately, he does not disclose how that can be achieved, especially if the product is already in a sealed container such as a can, jar or bottle. Nor does he mention how variations of initial product temperature within a batch can be identified or measured or can be accommodated within a continuous processing program. In all process controllers based on predictive processing algorithms, actual measurements are compared with the predictive program measurements and deviations identified.
Within a continuous sterilization system, there is very little opportunity to modify any of the processing parameters with the exception of dwell time. In practice, any under-processed containers can only be assured sufficient processing if the faulty product is identified before or within the sterilization chamber/tower as this is the only part of the process that actually reaches sterilization temperatures. If not identified in time then all product prior to and up to the point of identification has to considered suspect and either ejected or reprocessed which significantly enhances the likelihood of excessive over-processing and thus poorer quality. It also adds considerable additional cost.
Similarly, if under-processed product is identified in time and the conveyor speeds adjusted to ensure sufficient dwell time then because of the volumes of product these continuous systems process (often 400-600 units per minute), a very significant volume of ‘normally processed’ product will also become significantly over-processed.
All of the foregoing clearly show that current process controllers rely almost exclusively on the measurement and control of the processing parameters of the system and identify only when processing conditions actually or are likely to fail to meet minimum processing requirements. None measure any product variation in individual containers nor variations in energy transfer and none are able to modify processing conditions without over-processing ‘normal’ product. While such predictive process control algorithms ensure all product meets minimal sterilization requirements, it can only be done at the expense of significantly over-processing the majority of product.
We have found that it is impossible to both control product quality and achieve the most time-, quality- and cost-effective product processing without measuring and monitoring physical and chemical product variation on an individual container basis.
The technology and methods detailed in this patent application provide a unique and novel approach to resolving most, if not all such issues and problems and we will now detail the individual embodiments that comprise the solutions.